MultiTargetDB: a comprehensive database of multitarget ligands for polypharmacology research and drug discovery

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ID: 337853
2026
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Abstract
Multitarget drug discovery has gained considerable traction in recent years, particularly for the treatment of complex diseases. Despite the growing demand for dedicated, well-curated resources to advance polypharmacology research and rational multitarget drug discovery, such resources remain severely limited. Here, we present MultiTargetDB, a database of multitarget ligands integrated with comprehensive biological annotations and measurement-level provenance. At the small molecule level, MultiTargetDB integrates chemical structures (including molecular scaffolds), their drug development stages, and target information, whereas at the target level, MultiTargetDB incorporates protein domains and families, functional associations, and pathway-disease annotations. The current release contains 173 977 multitarget molecules, 6496 protein targets, and 474 749 standardized quantitative bioactivity records, complemented by 46 234 high-confidence protein functional associations, 370 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), and 2493 diseases. MultiTargetDB supports multitarget ligand retrieval, target-combination analysis, quantitative activity profiling, inspection of source-level evidence, and biological interpretation of molecule-target-pathway-disease relationships, with a natural-language query assistant facilitating flexible database exploration. The integrated quantitative, pharmacological and biological data further provide a basis for drug-repurposing exploration, computational modeling, and machine-learning applications. MultiTargetDB v1.0 is freely accessible at https://multitargetdb.inflygent.com/.
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openalex_W7225000796 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jinmei Pan, Haoyu Lin, Jintao Zhu, Weixin Xie, Yu Li, Jin Xie, Shuaipeng Zhang, Liangli Hong, Luhua Lai, Jianfeng Pei, Geng Dong
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Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag1097
URL
https://academic.oup.com/nar/advance-article-pdf/doi/10.1093/nar/gkag1097/72639873/gkag1097.pdf
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